corridorkey-mrp-mlx/prompts/phase3-conversion.md

Work only on checkpoint conversion.

Goal: Create a robust conversion pipeline from the PyTorch CorridorKey checkpoint to MLX-compatible weights.

Requirements:

• Inspect state_dict keys and map them explicitly.
• Convert conv weights from PyTorch layout to MLX layout.
• Preserve the patched 4-channel first conv behavior exactly.
• Write converter diagnostics:
  • source key
  • destination key
  • source shape
  • destination shape
  • transform applied
• Save output as safetensors or npz.
• Validate load with MLX strict loading wherever possible.

Do not:

• attempt full end-to-end model parity yet if Hiera is incomplete
• hide key mismatches
• use silent fallbacks

Definition of done:

• converter script exists
• mapping file exists
• shape validation passes for completed modules
• conversion report is readable and auditable